Method and system for heuristic location tracking

ABSTRACT

A method and system for provision of a notification based on location of a target device and heuristic information, the method maintaining, in a storage module, a location profile of a target mobile device based on heuristic information for the target mobile device; receiving the current location of the target mobile device; verifying whether the current location deviates from the location profile; and if the current location deviates from the location profile, triggering a notification to an observer device.

FIELD OF THE DISCLOSURE

The present disclosure relates to location tracking on a mobile deviceand in particular to location tracking based on heuristics.

BACKGROUND

Many mobile devices are now equipped with the ability to determine theirlocation and to report the location to others. While this provides manyadvantages, it also raises privacy issues, as some applications allowobservers to track the location of users anywhere, and anytime.

Specifically, it is useful and desirable to allow observers to track thelocation of mobile device users in some circumstances. In othercircumstances, this ability infringes upon the users' right to privacy.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure will be better understood with reference to thedrawings in which:

FIG. 1 is a block diagram showing an exemplary architecture for themethod and system of the present disclosure;

FIG. 2 is a block diagram of an exemplary learning method;

FIG. 3 is a block diagram illustrating the computation of the locationprofile according to one embodiment.

FIG. 4 is a block diagram of a method according to one embodiment; and

FIG. 5 is a block diagram of an exemplary user equipment capable ofbeing used with the present method and system.

DETAILED DESCRIPTION

According to one aspect of the present disclosure, there is provided amethod comprising: maintaining, in a storage module, a location profileof a target mobile device based on heuristic information for the targetmobile device; receiving the current location of the target mobiledevice; verifying whether the current location deviates from thelocation profile; and if the current location deviates from the locationprofile, triggering a notification to an observer device.

According to another aspect of the present disclosure, there is provideda network element comprising: a communication subsystem; a processor;memory; wherein the communications subsystem, processor and memorycooperate to: maintain, in a storage module, a location profile of atarget mobile device based on heuristic information for the targetmobile device; receive the current location of the target mobile device;verify whether the current location deviates from the location profile;and if the current location deviates from the location profile, triggera notification to an observer device.

The present disclosure is described below with regards to variousembodiments. Such embodiments are not intended to be limiting and couldbe modified by those skilled in the art and still be within the scope ofthe present disclosure. In particular, the present disclosure could beapplied to any location determination technology, such as GlobalPositioning System (GPS), Assisted GPS, and others.

The present disclosure relates to the tracking of at least one device byan observer while still considering privacy issues. This is done byusing the tracking device to collect data. The data is then analyzed andcompared to heuristic information to determine whether a notificationshould be triggered. The notification can be sent to an observer. Thetrigger is based on rules based on positional or other data, as providedbelow.

Reference is now made to FIG. 1, which shows an exemplary architecturefor one embodiment of a system in accordance with the presentdisclosure.

In FIG. 1, a target device 110 communicates with a mobile network 130.In one embodiment, target device 110 is a mobile device and network 130is a wireless network. Such a network can include, but is not limited toa Code Division Multiple Access (CDMA) network, a Global System forMobile communications (GSM), Universal Mobile Terrestrial System (UMTS),Long Term Evolution (LTE), Long Term Evolution Advanced (LTE-A), amongothers. In other embodiments network 130 can include an access point andbe a WiFi™ or WiMAX™ system. Other networks 130 will be known to thoseskilled in the art.

Network 130 can communicate with a further IP network 132 such as theInternet, which may communicate, in some cases, with a wide area network(WAN) 134.

An observer 120 or 122 can also communicate with network 130 throughwired or wireless communication channels. For example, observer 120 maybe a mobile device or observer 122 may be a fixed computer.

A server 140 may further communicate with observer 120 or 122 throughnetwork 130, typically through IP network 132. Server 140 may be used insome embodiments where privacy requires that raw information not be sentto an observer 120 or 122.

Target device 110 may be any mobile device. Mobile devices are known tothose in the art and can also be referred to as a mobile terminal,mobile station, personal digital assistant, smart phone, laptop, amongothers.

In the first portion of the present method, which will hereinafter bereferred to as the “learning phase”, a tracked mobile device collectslocation information at intervals in order to build a location history,or a location profile for the mobile device.

For example, according to a non-limiting embodiment of the presentmethod, a mobile device builds its location history or profile(hereinafter, the terms ‘history’ and ‘profile’ are usedinterchangeably) based on a 24 hour cycle and 1 hour intervals. In thisembodiment, the mobile device collects its location data once every hourand analyzes readings made at the same time of day together.

Specifically, if a location reading is taken at 9 AM on a first day,subsequent readings will occur at 10 AM, 11 AM, noon, 1 PM, and so on.For analysis purposes, the location reading taken at 9 AM on thefollowing day will be compared with the location reading taken at 9 amon the first day. As would be appreciated by those skilled in the art,the above is merely an example, and other cycles than 24 hours or otherintervals than one hour are also possible.

The length of the learning phase can vary between embodiments. In atypical embodiment, the learning phase would last for 10 to 20 cycles.In other embodiments, the learning phase is ongoing and the locationprofile is continuously refined. In yet another embodiment, the learningphase may continue until certain conditions are met. For example, insome embodiments, the learning phase may continue until the standarddeviation calculated for each time interval within a cycle is less thana threshold.

The results of the location readings are then stored and analyzed inorder to create the user's location profile. In one embodiment, thereadings are stored and analyzed on the mobile device. In otherembodiments, the readings are transferred to the observer device forstorage and analysis. In yet another embodiment, the readings aretransferred to an application server on the network.

In some embodiments, the readings are transferred to the observer deviceor an application server using a secure data protocol.

In embodiments where the readings are transferred to the observer devicefor storage and analysis, the readings should remain invisible to theuser of the observer device, as they represent the raw location data ofthe tracked mobile device.

The above is shown, for example, with reference to FIG. 2. The processof FIG. 2 starts at block 210 and proceeds to block 212 in which a checkis made to determine whether it is time to take a reading. If not theprocess continues to loop to block 212 until it is time to take areading. As will be appreciated by those in the art having regard to thepresent disclosure, the check of block 212 can be implemented in avariety of ways including a timer, an interrupt, among other options.

From block 212, the process proceeds to block 214 in which a locationreading is taken. The location reading of block 214 can utilize aninternal Global Positioning System (GPS) within the device, assisted GPSusing a base station, an external GPS communicating with the devicethrough short range communications, among other options.

From block 214 the process may optionally proceed to block 216 tocollect other heuristic data. For example in block 216 data from anaccelerometer may be recorded, data from a temperature sensor may berecorded or other data from external or internal sensors may beutilized. The present disclosure is not limited by any such sensor ordata.

From block 216, or from block 214 if block 216 is not used, the processproceeds to block 218 in which the data is stored. The data may bestored on the device being tracked or may be reported directly to anobserver to store the data on the observer's device.

From block 218 the process proceeds to block 220 to check whether thelearning period or stage is over. If no the process proceeds to block212 to determine the next time to take a reading.

If it is determined in block 220 that the learning period is over theprocess proceeds to block 230 and ends the learning process.

As new readings are taken and stored, the device on which they arestored (the tracked device, observer device, or an application server)performs an analysis to create a location profile for the mobile device.

The purpose of the location profile is to enable the detection ofsignificant deviations from a user's usual traveling habits in order toalert the observer of such a deviation. Accordingly, the locationprofile can be computed in a number of ways, as long as this objectiveis achieved.

In one embodiment, described in greater detail below, the locationprofile is based on a normal distribution of locations for each readingtime. Other methods of computing a location profile are also within thescope of the present disclosure.

In this embodiment, an average position for each interval within thecycle is calculated, as is the standard deviation for the position,using standard statistical techniques. An example is provided in FIG. 3.

In FIG. 3, location readings 310, 312, 316 and 318 were all made duringthe learning phase. The average location reading is shown at 320. Acircle 330, centered around average location 320, has a radius which iscomputed as a function of the standard deviation. For example, in oneembodiment, the radius of circle 330 is equal to 3 times the standarddeviation.

At a time after the learning phase, a location reading 340 is made. Asreading 340 is outside of circle 330, it is deemed to be unusual and theobserver is notified. In one embodiment, the observer is simply notifiedthat the tracked user has deviated from his location profile withoutproviding further details. In another embodiment, the observer isnotified of the extent by which the tracked user has deviated, and inyet another embodiment, the notification could include the exactlocation of the tracked user when the reading took place.

In some embodiments, the learning phase might be constrained by ruleswhich would ensure greater data integrity. For example, on someoccasions, the user might travel far from its usual destinations, andreadings taken on such occasions would contaminate the data.

Accordingly, in one embodiment, the user may be allowed to turn off thelearning mode temporarily. In another embodiment, readings which are toofar (according to, for example, a threshold value) from an existingaverage value are simply discarded for the purposes of the learningphase.

Based on the above, a tracked user's behavior is learned.

Reference is now made to FIG. 4, which shows a block diagram of a methodaccording to the above embodiment. The learning phase of FIG. 2 has beencompleted prior to the process of FIG. 4 being used.

The process starts at block 410 and proceeds to block 430 in which thetracked mobile device reads its current location. In some embodiments,this may occur at fixed times which may or may not correspond to theintervals of the cycle during the learning phase. In other embodiments,the mobile device may read its current location almost continuously. Inyet further embodiments, the reading may be based on polling by theobserver.

From block 430 the process proceeds to block 440, in which a check ismade to determine whether the current location is within the expectedrange. As per the above, the check may be computed at the target device,an application server, or the observer device. In that case, the currentlocation is sent to the observer device or the application server priorto determining whether the current location is within the expectedrange.

As discussed above, the expected range is typically the average locationfor a given time, plus a function of the standard deviation as computedduring the learning phase.

Further, the reading of block 430 and calculation of block 440 caninclude other data from the target device, such as accelerometerreadings, temperature readings, available network readings, batterylevel, or other data known to the target device.

If the location is within the expected range, or if other rules totrigger a notification are not met, the method ends at block 460 until anew measurement is made. Once the new measurement is made, the processstarts again from block 430.

If the check of block 440 causes a notification trigger, the processproceeds to block 350, where the observer is notified. From block 450the process then proceeds to block 360 and ends until anothermeasurement is made.

The above method could be further refined by allowing either theobserver or the user to set rules for determining when to notify theobserver.

For example, a rule could be set by the observer, so that the observeris notified of only the second deviation by the user in a given day.Another rule could specify a threshold distance from the averagelocation, beyond which the observer would be notified. As would beappreciated by those skilled in the art, such a rule could be set tooverride the error range computed as a function of the standarddeviation in some embodiments.

Yet another kind of rule could allow the observer or the user to definea large area, in which the user is expected to be at given times. Forexample, if the user is a student at a university, the areacorresponding to the university campus could be entered into the system,via the user's mobile device or the observer's mobile device, and theobserver would be notified when the user is a certain distance away fromthe campus at a relevant time.

In some cases, it may be desirable to notify the observer that thetracked mobile device is in a particular location, irrespective of theuser's location history. For example, a parent may want to be notifiedif his or her child is venturing into a dangerous area of a city. Inthis scenario, the parent could configure the notification applicationto notify the observer anytime the tracked user enters an areadesignated as dangerous, or simply prohibited, by the parent.

The above rules are only provided as examples, and any number of rulescould be implemented as would be appreciated by those skilled in theart.

The above rules can be implemented in block 440 of FIG. 4 to checkwhether a rule has been satisfied by the latest reading. As would beappreciated by those skilled in the art, all data pertaining to theserules will need to be transferred from the device on which the ruleswere entered to the device on which the analysis portion of the methodis performed.

In other embodiments, the present method and apparatus can also learn aprofile, and detect deviation from the profile, based on more parametersthan just location.

Many mobile devices today are equipped with a whole array of sensors,including but not limited to, accelerometers, sensors for measuringtemperature, luminosity, and atmospheric pressure. These sensors cancollect data similarly to the location detection means for use in thepresent method.

For example, temperature data could be collected and correlated withother data such as time, and data from other sensors. The collected datawould then be analyzed for pattern recognition, allowing the system todetect future deviations from established patterns.

In one embodiment, temperature data is collected continuously from atemperature sensor on a mobile device. As this data is of significantsize, in most cases it will be preferable to store the data locally,however, it may also be advantageous to transfer the data to a server oran observer device for storage.

The stored temperature data is then analyzed for pattern recognition. Inone example, the data may reveal a pattern which suggests that for 15 to20 minutes everyday, around 10:30 am, the temperature dropssignificantly from the temperature observed throughout the day. Thiscould be caused by the user of the mobile device going out during recessat school.

If, at one point after the pattern has been learned by the system, theuser of the mobile device fails to go out during recess, or if the userremains outside for significantly longer than usual, the system willdetect this deviation from established patterns, and notify an observer.

As would be appreciated by those skilled in the art, the above exampleis merely illustrative and any type of sensor could be used to collectdata. Furthermore, any number of sensor can be used to generate data,and data from various sensors may be correlated against each other inorder to extract meaningful patterns.

In these cases, as in the location and temperature cases discussedabove, the data from the sensors is stored and analyzed for patternrecognition. When an event deviates significantly from the establishedpatterns, the observer device is notified as described above.

In other embodiments, an observer device may be notified according torules set by the observer, as described above with respect to location.Under this scenario, the user of the observer device (also referred toherein as the “observer”), sets conditions based on the various sensordata collected by the observed device. As will be appreciated by thoseskilled in the art, these conditions may or may not relate to patternsdetected during the learning phase. When these conditions are met, theobserver device is notified.

The notification may also vary depending on severity. For example, achild leaving a school by foot, as determined by an accelerometer, maytrigger a low severity notification to a parent. The notification maysimply be that the child has left the school premises at a certain time.Conversely, a child leaving a school by vehicle may cause more concernto a parent, and more information such as the road that the child is onor even the exact location of the child may be provided in this case.

Thus the trigger of block 440 could have various severity levels and thenotification of block 450 may provide different information levels basedon the severity of the trigger.

Based on the above, a target device 110 may include software or programcode to determine a location and other data that may be relevant to anobserver. In one embodiment target device may also include software fornotifying an observer. In this case, raw data may never be sent across anetwork and instead the notification software may make a determinationof whether an alert or notification should be sent.

In other embodiments, the target 110 may sent the information tonotification software located either on server 140 or on an observerdevice 120 or 122. If the information is sent to an observer device 120or 122, software within the device may prevent the disclosure of the rawinformation to the user of the observer device 120 or 122.

If the raw data is sent to server 140, server 140 can make thedetermination, utilizing software on the server 140, of whether to senda notification to observer 120 or 122.

In each case, device 110, 120, 122 or 130 include a processor and memoryto execute program code to analyze the data and determine whether anotification should be triggered.

Target device 110 or observer device 120 can be any mobile device. Onesuch exemplary mobile device is illustrated below with reference to FIG.5. The mobile device of FIG. 5 is however not meant to be limiting andother mobile devices could also be used.

Mobile device 500 is typically a two-way wireless communication devicehaving voice and data communication capabilities. Mobile device 500generally has the capability to communicate with other devices orcomputer systems. Depending on the exact functionality provided, themobile device may be referred to as a data messaging device, a two-waypager, a wireless e-mail device, a cellular telephone with datamessaging capabilities, a wireless Internet appliance, a wirelessdevice, a user equipment, or a data communication device, as examples.

Where mobile device 500 is enabled for two-way communication, it willincorporate a communication subsystem 511, including both a receiver 512and a transmitter 514, as well as associated components such as one ormore antenna elements 516 and 518, local oscillators (LOs) 513, and aprocessing module such as a digital signal processor (DSP) 520. As willbe apparent to those skilled in the field of communications, theparticular design of the communication subsystem 511 will be dependentupon the communication network in which the device is intended tooperate.

Network access requirements will also vary depending upon the type ofnetwork 519. In some networks, network access is associated with asubscriber or user of mobile device 500. A mobile device may require aremovable user identity module (RUIM) or a subscriber identity module(SIM) card in order to operate on the network. The SIM/RUIM interface544 may be similar to a card-slot into which a SIM/RUIM card can beinserted and ejected like a diskette or PCMCIA card. The SIM/RUIM cardcan have memory and hold many key configuration 551, and otherinformation 553 such as identification, and subscriber relatedinformation.

When required network registration or activation procedures have beencompleted, mobile device 500 may send and receive communication signalsover the network 519. As illustrated in FIG. 5, network 519 can consistof multiple base stations communicating with the mobile device. Forexample, in a hybrid CDMA 1×EVDO system, a CDMA base station and an EVDObase station communicate with the mobile station and the mobile deviceis connected to both simultaneously. In other systems such as Long TermEvolution (LTE) or Long Term Evolution Advanced (LTE-A), multiple basestations may be connected to for increased data throughput. Othersystems such as GSM, GPRS, UMTS, HSDPA, among others are possible andthe present disclosure is not limited to any particular cellulartechnology.

Signals received by antenna 516 through communication network 519 areinput to receiver 512, which may perform such common receiver functionsas signal amplification, frequency down conversion, filtering, channelselection and the like, and in the example system shown in FIG. 5,analog to digital (A/D) conversion. A/D conversion of a received signalallows more complex communication functions such as demodulation anddecoding to be performed in the DSP 520. In a similar manner, signals tobe transmitted are processed, including modulation and encoding forexample, by DSP 520 and input to transmitter 514 for digital to analogconversion, frequency up conversion, filtering, amplification andtransmission over the communication network 519 via antenna 518. DSP 520not only processes communication signals, but also provides for receiverand transmitter control. For example, the gains applied to communicationsignals in receiver 512 and transmitter 514 may be adaptively controlledthrough automatic gain control algorithms implemented in DSP 520.

Mobile device 500 generally includes a processor 538 which controls theoverall operation of the device. Communication functions, including dataand voice communications, are performed through communication subsystem511. Processor 538 also interacts with further device subsystems such asthe display 522, flash memory 524, random access memory (RAM) 526,auxiliary input/output (I/O) subsystems 528, serial port 530, one ormore keyboards or keypads 532, speaker 534, microphone 536, othercommunication subsystem 540 such as a short-range communicationssubsystem and any other device subsystems generally designated as 542.Serial port 530 could include a USB port or other port known to those inthe art having the benefit of the present disclosure.

Some of the subsystems shown in FIG. 5 perform communication-relatedfunctions, whereas other subsystems may provide “resident” or on-devicefunctions. Notably, some subsystems, such as keyboard 532 and display522, for example, may be used for both communication-related functions,such as entering a text message for transmission over a communicationnetwork, and device-resident functions such as a calculator or tasklist, among other applications.

Operating system software used by the processor 538 may be stored in apersistent store such as flash memory 524, which may instead be aread-only memory (ROM) or similar storage element (not shown). Thoseskilled in the art will appreciate that the operating system, specificdevice applications, or parts thereof, may be temporarily loaded into avolatile memory such as RAM 526. Received communication signals may alsobe stored in RAM 526.

As shown, flash memory 524 can be segregated into different areas forboth computer programs 558 and program data storage 550, 552, 554 and556. These different storage types indicate that each program canallocate a portion of flash memory 524 for their own data storagerequirements. The applications may be segregated based on the mode orcategory they fall into. Memory 524 may further provide security forcorporate data and if some applications are locked while others are not.

Processor 538, in addition to its operating system functions, may enableexecution of software applications on the mobile device. A predeterminedset of applications that control basic operations, including at leastdata and voice communication applications for example, will normally beinstalled on mobile device 500 during manufacturing. Other applicationscould be installed subsequently or dynamically.

Applications and software, such as those for implements the process ofFIGS. 2, 3 and 4, may be stored on any computer readable storage medium.The computer readable storage medium may be a tangible orintransitory/non-transitory medium such as optical (e.g., CD, DVD,etc.), magnetic (e.g., tape) or other memory known in the art.

One software application may be a personal information manager (PIM)application having the ability to organize and manage data itemsrelating to the user of the mobile device such as, but not limited to,e-mail, calendar events, voice mails, appointments, and task items.Naturally, one or more memory stores would be available on the mobiledevice to facilitate storage of PIM data items. Such PIM application mayhave the ability to send and receive data items, via the wirelessnetwork 519. In one embodiment, the PIM data items are seamlesslyintegrated, synchronized and updated, via the wireless network 519, withthe mobile device user's corresponding data items stored or associatedwith a host computer system. Further applications may also be loadedonto the mobile device 500 through the network 519, an auxiliary I/Osubsystem 528, serial port 530, short-range communications subsystem 540or any other suitable subsystem 542, and installed by a user in the RAM526 or a non-volatile store (not shown) for execution by the processor538. Such flexibility in application installation increases thefunctionality of the device and may provide enhanced on-devicefunctions, communication-related functions, or both. For example, securecommunication applications may enable electronic commerce functions andother such financial transactions to be performed using the mobiledevice 500.

In a data communication mode, a received signal such as a text messageor web page download will be processed by the communication subsystem511 and input to the processor 538, which may further process thereceived signal for output to the display 522, or alternatively to anauxiliary I/O device 528.

A user of mobile device 500 may also compose data items such as emailmessages for example, using the keyboard 532, which may be a completealphanumeric keyboard or telephone-type keypad, among others, inconjunction with the display 522 and possibly an auxiliary I/O device528. Such composed items may then be transmitted over a communicationnetwork through the communication subsystem 511.

For voice communications, overall operation of mobile device 500 issimilar, except that received signals would typically be output to aspeaker 534 and signals for transmission would be generated by amicrophone 536. Alternative voice or audio I/O subsystems, such as avoice message recording subsystem, may also be implemented on mobiledevice 500. Although voice or audio signal output is preferablyaccomplished primarily through the speaker 534, display 522 may also beused to provide an indication of the identity of a calling party, theduration of a voice call, or other voice call related information forexample.

Serial port 530 in FIG. 5 would normally be implemented in a personaldigital assistant (PDA)-type mobile device for which synchronizationwith a user's desktop computer (not shown) may be desirable, but is anoptional device component. Such a port 530 would enable a user to setpreferences through an external device or software application and wouldextend the capabilities of mobile device 500 by providing forinformation or software downloads to mobile device 500 other thanthrough a wireless communication network. The alternate download pathmay for example be used to load an encryption key onto the devicethrough a direct and thus reliable and trusted connection to therebyenable secure device communication. As will be appreciated by thoseskilled in the art, serial port 530 can further be used to connect themobile device to a computer to act as a modem.

Other communications subsystems 540, such as a short-rangecommunications subsystem, is a further optional component which mayprovide for communication between mobile device 500 and differentsystems or devices, which need not necessarily be similar devices. Forexample, the subsystem 540 may include an infrared device and associatedcircuits and components or a Bluetooth™ communication module to providefor communication with similarly enabled systems and devices.

The embodiments described herein are examples of structures, systems ormethods having elements corresponding to elements of the techniques ofthis application. This written description may enable those skilled inthe art to make and use embodiments having alternative elements thatlikewise correspond to the elements of the techniques of thisapplication. The intended scope of the techniques of this applicationthus includes other structures, systems or methods that do not differfrom the techniques of this application as described herein, and furtherincludes other structures, systems or methods with insubstantialdifferences from the techniques of this application as described herein.

The embodiments described herein are examples of structures, systems ormethods having elements corresponding to elements of the techniques ofthis application. This written description may enable those skilled inthe art to make and use embodiments having alternative elements thatlikewise correspond to the elements of the techniques of thisapplication. The intended scope of the techniques of this applicationthus includes other structures, systems or methods that do not differfrom the techniques of this application as described herein, and furtherincludes other structures, systems or methods with insubstantialdifferences from the techniques of this application as described herein.

1. A method comprising: maintaining, in a storage module, a locationprofile of a target mobile device based on heuristic information for thetarget mobile device; receiving the current location of the targetmobile device; verifying whether the current location deviates from thelocation profile; and if the current location deviates from the locationprofile, triggering a notification to an observer device.
 2. The methodof claim 1, wherein the location profile is created during a learningphase.
 3. The method of claim 2, wherein the location profile includesan expected location and an error range for each time period of a timecycle.
 4. The method of claim 3, further comprising the step of: lookingup the expected location and the error range for the current time periodof the time cycle; and determining whether the current location iswithin an area defined by the expected location and the expected errorrange.
 5. The method of claim 4, where in the learning phase comprises:during each time period of the time cycle, and for N time cycles,reading the current location of the target mobile device; computing anaverage and a standard deviation of the location for each period withinthe time cycle; wherein N is a positive integer.
 6. The method of claim5 wherein the error range for each time period of the time cycle is afunction of the standard deviation for the time period.
 7. The method ofclaim 1, wherein the storage module is on the observer device, targetmobile device or an application server.
 8. The method of claim 1,wherein the triggering of the notification at the observer device alsonotifies the observer device of the extent by which the current locationdeviates from the average.
 9. The method of claim 1, further includingthe steps of: maintaining a list of prohibited geographical areas; andafter the step of reading the current location, if the current locationis within a prohibited area of the list of prohibited geographicalareas, notifying the observer device.
 10. The method of claim 1, whereinthe verifying step comprises: evaluating each one of a set of rulesbased on said current location; if at least one rule of the set of rulesis satisfied during the evaluating step, notifying the observer device.11. The method of claim 1, further comprising receiving supplementarydata for the target mobile device, wherein the verifying utilizes thesupplementary data in determining whether to trigger a notification. 12.The method of claim 11, wherein the verifying utilizes rules related tothe supplemental data and location to determine whether to trigger thenotification.
 13. The method of claim 1, wherein the triggering anotification includes a severity for the trigger, said severity varyingdata disclosure in a notification.
 14. A network element comprising: acommunication subsystem; a processor; memory; wherein the communicationssubsystem, processor and memory cooperate to: maintain, in a storagemodule, a location profile of a target mobile device based on heuristicinformation for the target mobile device; receive the current locationof the target mobile device; verify whether the current locationdeviates from the location profile; and if the current location deviatesfrom the location profile, trigger a notification to an observer device.15. The network element of claim 14, wherein the location profileincludes an expected location and an error range for each time period ofa time cycle.
 16. The network element of claim 15, wherein thecommunications subsystem, processor and memory further cooperate to:look up the expected location and the error range for the current timeperiod of the time cycle; and determine whether the current location iswithin an area defined by the expected location and the expected errorrange.
 17. The network element of claim 16, wherein the communicationssubsystem, processor and memory further cooperate to: during each timeperiod of the time cycle, and for N time cycles, read the currentlocation of the target mobile device; and compute an average and astandard deviation of the location for each period within the timecycle; wherein N is a positive integer.
 18. The network element of claim17 wherein the error range for each time period of the time cycle is afunction of the standard deviation for the time period.
 19. The networkelement of claim 14, wherein the communications subsystem, processor andmemory cooperate to trigger the notification by notifying an observerdevice of the extent by which the current location deviates from theaverage.
 20. The network element of claim 14, wherein the communicationssubsystem, processor and memory further cooperate to: maintain a list ofprohibited geographical areas; and after reading the current location,if the current location is within a prohibited area of the list ofprohibited geographical areas, notify the observer device.
 21. Thenetwork element of claim 14, wherein the communications subsystem,processor and memory cooperate to verify by: evaluating each one of aset of rules based on said current location; if at least one rule of theset of rules is satisfied during the evaluating, notifying the observerdevice.
 22. The network element of claim 14, wherein the communicationssubsystem, processor and memory cooperate to receive supplementary datafor the target mobile device, wherein the verifying utilizes thesupplementary data in determining whether to trigger a notification. 23.The network element of claim 22, wherein the verifying utilizes rulesrelated to the supplemental data and location to determine whether totrigger the notification.
 24. The network element of claim 14, whereinthe triggering a notification includes a severity for the trigger, saidseverity varying data disclosure in a notification.
 25. The networkelement of claim 14, wherein the network element is the observer device,target mobile device or an application server.